Adapting and Validating a Scale to Measure Sexual Stigma among Lesbian, Bisexual and Queer Women
Bibliographic record
Abstract
Lesbian, bisexual and queer (LBQ) women experience pervasive sexual stigma that harms wellbeing. Stigma is a multi-dimensional construct and includes perceived stigma, awareness of negative attitudes towards one's group, and enacted stigma, overt experiences of discrimination. Despite its complexity, sexual stigma research has generally explored singular forms of sexual stigma among LBQ women. The study objective was to develop a scale to assess perceived and enacted sexual stigma among LBQ women. We adapted a sexual stigma scale for use with LBQ women. The validation process involved 3 phases. First, we held a focus group where we engaged a purposively selected group of key informants in cognitive interviewing techniques to modify the survey items to enhance relevance to LBQ women. Second, we implemented an internet-based, cross-sectional survey with LBQ women (n=466) in Toronto, Canada. Third, we administered an internet-based survey at baseline and 6-week follow-up with LBQ women in Toronto (n=24) and Calgary (n=20). We conducted an exploratory factor analysis using principal components analysis and descriptive statistics to explore health and demographic correlates of the sexual stigma scale. Analyses yielded one scale with two factors: perceived and enacted sexual stigma. The total scale and subscales demonstrated adequate internal reliability (total scale alpha coefficient: 0.78; perceived sub-scale: 0.70; enacted sub-scale: 0.72), test-retest reliability, and construct validity. Perceived and enacted sexual stigma were associated with higher rates of depressive symptoms and lower self-esteem, social support, and self-rated health scores. Results suggest this sexual stigma scale adapted for LBQ women has good psychometric properties and addresses enacted and perceived stigma dimensions. The overwhelming majority of participants reported experiences of perceived sexual stigma. This underscores the importance of moving beyond a singular focus on discrimination to explore perceptions of social judgment, negative attitudes and social norms.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".